A Novel Grey Seasonal Model for Natural Gas Production Forecasting

Abstract

To accurately predict the time series of energy data, an optimized Hausdorff fractional grey seasonal model was proposed based on the complex characteristics of seasonal fluctuations and local random oscillations of seasonal energy data. This paper used a new seasonal index to eliminate the seasonal variation of the data and weaken the local random fluctuations. Furthermore, the Hausdorff fractional accumulation operator was introduced into the traditional grey prediction model to improve the weight of new information, and the particle swarm optimization algorithm was used to find the nonlinear parameters of the model. In order to verify the reliability of the new model in energy forecasting, the new model was applied to two different energy types, hydropower and wind power. The experimental results indicated that the model can effectively predict quarterly time series of energy data. Based on this, we used China’s quarterly natural gas production data from 2015 to 2021 as samples to forecast those for 2022–2024. In addition, we also compared the proposed model with the traditional statistical models and the grey seasonal models. The comparison results showed that the new model had obvious advantages in predicting quarterly data of natural gas production, and the accurate prediction results can provide a reference for natural gas resource allocation.

Advanced Mathematical Approaches in Psycholinguistic Data Analysis: A Methodological Insight

“…It offers tangible insights for linguistic research, showcasing the pivotal role of fractile regression and resampling methods in decoding real-world linguistic patterns. Such an application accentuates the relevance of these methods in revealing nuanced patterns, aligning with the FF principles [2,6,8,9].…”

“…Complexity and non-linearity: Utilizing fractile regression allows us to address the significant asymmetries (skewness) present in the distributions of our data and to embrace their inherent non-linear characteristics [2,6]. This alignment with the complexities is in tune with the FF philosophy of interpreting non-linear patterns [8,9].…”

“…Interestingly, other disciplines have adapted to the intricacies of this type of data by adopting innovative models. One example involves the use of the grey seasonal model in natural gas production, which underscores the capabilities of advanced techniques [6]. In contrast, psycholinguistics still predominantly relies on conventional methodologies, which may not adequately cater to the rising complexities in data.…”

Utilizing a Fractional-Order Grey Model to Predict the Development Trends of China’s Electronic Commerce Service Industry

“…This theory provides a feasible solution for analysis and decisionmaking problems under the condition of small data sets and is widely used in different application fields, such as engineering, manufacturing, business, etc. [7][8][9][10][11][12][13]. Grey modeling is an important branch of grey system theory and is mainly used for the extraction of pattern trends from small data sets [14].…”

“…Use Equation (7) to output the estimated value of the r-order accumulated generating series X(r) = x(r) (1), x(r) (2), . .…”